Polarization image-based building inspection
Systems of this disclosure enable building inspection using polarization images. The systems use light polarization information of the polarization images to detect misapplications of tape applied to a substrate. An example system includes polarization camera hardware, a memory communicatively coupled to the polarization camera hardware, and processing circuitry communicatively coupled to the memory. The polarization camera hardware is configured to capture a polarization image of a tape as applied to a substrate. The memory is configured to store the polarization image. The processing circuitry is configured to analyze the polarization image according to a trained classification model and, based on the analysis of the polarization image according to the trained classification model, detect a misapplication with respect to the tape as applied to the substrate.
1 . A system comprising:
polarization camera hardware configured to capture a polarization image of a tape as applied to an envelope layer of a building;
a memory communicatively coupled to the polarization camera hardware, the memory being configured to store the polarization image; and
processing circuitry communicatively coupled to the memory, the processing circuitry being configured to:
analyze the polarization image according to a trained classification model; and
based on the analysis of the polarization image according to the trained classification model, detect a misapplication with respect to the tape as applied to the envelope layer of the building, the misapplication being associated with at least one of a fishmouth crease or a crease in the tape as applied to the envelope layer of the building.
2 . The system of claim 1 , wherein the trained classification model is a trained neural network model.
3 . The system of claim 1 , wherein the polarization camera hardware is integrated into a mobile computing device.
4 . The system of claim 1 , wherein the polarization camera hardware is communicatively coupled to a mobile computing device.
5 . The system of claim 3 , wherein the mobile computing device comprises one of a smartphone, a tablet computer, or a wearable computing device.
6 . The system of claim 1 , wherein the polarization camera hardware is communicatively coupled to a drone.
7 . The system of claim 1 , wherein the polarization camera hardware is integrated into a drone.
8 . The system of claim 1 , further comprising output hardware communicatively coupled to the processing circuitry, wherein the processing circuitry is further configured to output, via the output hardware, a model output indicative of the misapplication of the tape as applied to the envelope layer of the building.
9 . The system of claim 1 , wherein the trained classification model is configured to implement one or more of full-image classification, sub-image classification, object detection, or image segmentation with respect to the polarization image.
10 . The system of claim 1 , wherein the polarization image indicates division of focal plane (DoLP) data with respect to the tape as applied to the envelope layer of the building.
11 . A method comprising:
capturing, by polarization camera hardware, a polarization image of a tape as applied to an envelope layer of a building;
analyzing, by processing circuitry communicatively coupled to the image capture hardware, the polarization image according to a trained classification model; and
detecting, by the processing circuitry, based on the analysis of the polarization image according to the trained classification model, a misapplication with respect to the tape as applied to the envelope layer of the building, the misapplication being associated with at least one of a fishmouth crease or a crease in the tape as applied to the envelope layer of the building.
12 . The method of claim 11 , wherein the trained model is a trained neural network model.
13 . The method of claim 11 , wherein the polarization camera hardware is integrated into a mobile computing device.
14 . The method of claim 11 , wherein the polarization camera hardware is integrated into a drone.
15 . The method of claim 11 , further comprising outputting, by the processing circuitry, via output hardware communicatively coupled to the processing circuitry, a model output indicative of the misapplication of the tape as applied to the envelope layer of the building.
16 . The method of claim 11 , wherein the trained model is configured to implement one or more of full-image classification, sub-image classification, object detection, or image segmentation with respect to the polarization image.
17 . The method of claim 11 , wherein the polarization image indicates division of focal plane (DoLP) data with respect to the tape as applied to the envelope layer of the building.
18 . A computer-readable storage device encoded with instructions that, when executed, cause processing circuitry of a computing device to:
receive, from polarization camera hardware, a polarization image of a tape as applied to an envelope layer of a building;
store the polarization image to the computer-readable storage device;
analyze the polarization image according to a trained model; and
based on the analysis of the polarization image according to the trained model, detect a misapplication with respect to the tape as applied to the envelope layer of the building, the misapplication being associated with at least one of a fishmouth crease or a crease in the tape as applied to the envelope layer of the building.